Database Tables
A database typically contains a catalog that describes its various elements. The catalog divides the database into sub-databases known as schemas. Within each schema are tables. FIG. 1 shows an exemplary database table 100. A database table consists of rows C1-CN and columns R1-RN. The columns of a table are accessed and identified by name. For example, the name for column C3 might be “Phone#” and the name for column C6 might be “Social Security Number”.
Each column typically has a defined data type where the value for the column in each row is supposed to be of the column's defined data type (or a null). Thus, continuing with the example above, the data type for the “Phone#” column C3 might be a ten digit string whereas the data type for the “Social Security Number” column C6 might be a nine digit string. Each value of column C3 would therefore be a ten digit number or a null value; and, likewise each value of column C6 would be a nine digit string or a null value.
The primary key for a table is a designated set of one or more columns whose values are unique for each table row. As a consequence, the primary key can be used to identify a particular row. For example, assume that the table described above contained information concerning certain individuals (e.g., their salary, tax records, investment information, etc.) where a separate row was used to hold all of the data for each individual. Here, given that there exists some likelihood that two different individuals might have the same name but practically no likelihood that two different individuals will have the same phone number and social security number, columns C3 and C6 could be used as the primary key for the table.
That is, presenting an individual's phone number and social security number as input information to the table 100 would be sufficient to uniquely identify the row in the table where the individual's data is recorded. As such, a row in any table within an entire database can be uniquely defined by: 1) the identity of the table (i.e., the Table ID); and, 2) the row's primary key values.
Data Dictionaries and Database Software/Drivers
In the realm of enterprise software, certain software functions have evolved into significant architectural components. Two of these, the data dictionary 201 and the SQL based database interface 204 are shown in FIG. 2. A database dictionary 201 provides as an output 203 a description of the organization of a database. Included in this information would be, for example, the number of columns in a particular table, the number of rows in a particular table, which columns of the table are the primary keys, etc.
The output 203 is provided in response to some indication of the information desired. FIG. 2 shows a particular data dictionary example that provides the structure of a table (which, for example, might include a description of the column strategy C1-Cx as depicted in FIG. 2) in response to an input that identifies the table (i.e., the Table ID).
The database dictionary output information 203 is typically used to determine the format for a Structured Query Language (SQL) database command 206 that is provided to an SQL based database interface 204 (also referred to in the art as “database software” or a “database driver”). An SQL based database interface 204 is the communicative focal point between a database and the software users (e.g., applications, transactions, sessions, etc.) that use its information.
Frequently, an SQL command is a read that requests information from the database 205 or a write that seeks to write new information into the database 205. The SQL based database interface 204 provides a response 207 to a read in the form of the data desired and to a write, typically, in the form of an acknowledgement that the write was successful. When information within a database table is to be accessed, the SQL command used to trigger the access may be structured in a way that resembles the table's organization. Here, the information 203 provided by a data dictionary 201 may be used to help build the SQL command 206.
Logical Locking
Because two different users may simultaneously desire the same data, most database management schemes permit database data to be locked. Traditionally, locking has been “physical” in the sense that the locking is performed by the database itself.
In contrast to physical locking, logical locking is a technique in which locking is controlled at a higher level of abstraction from the physical database(s). For example, according to one type of implementation, the logical locking function is executed upon a “lock server” that controls database locking activity separately from one or more database servers. By controlling locking in a remote fashion relative to the database(s), inefficiencies associated with physical locking may be avoided.
For example, logical locking should allow for better cohesiveness of software that depends upon databases having disparate physical locking characteristics (e.g., where a first database is able to lock a single row and another database is only able to lock a group of rows). The abstract remoteness of logical locking (with respect to physical locking) may also permit items other than database entries to be locked. For example, in an object-oriented environment, data objects having no relationship to any database could conceivably be locked (as well as database entries as described above). Moreover complex locking relationships may be implemented. For example, if an object that represents “an order” is to be locked, all other objects that represent items in the order may be automatically locked in response.
FIG. 3 shows a prior art logical locking interface 301. An interface (such as an Application Programmer's Interface (API)) is a defined set of inputs (e.g., commands, parameters, etc.) to a first software function that can be invoked by a second software function so that the second software function can use the first software function. Software interfaces also typically provide for the presentation of output information that is responsive to one or more of the inputs.
As described in more detail below, the information that is to be locked is defined at the logical locking interface 301 along with a request to lock it. The functionality behind the logical locking interface 301 (i.e., the software function that the logical locking interface 301 serves as a user interface for) analyzes each lock request and grants/rejects each lock request for a data item based upon the non-existence/existence of a lock for the same item of data.
The logical locking interface 301 of FIG. 3 has a name input 302 and an argument input 303. The name input 302 identifies “the owner” of the item of data for which a lock is being requested. The argument input 303 identifies the item of data that a lock is being requested for. The functionality behind the locking interface is “name based” in the sense that every data item that is capable of being locked is assumed to belong to an owner having a specific name. For example, if a data field within an object is to be locked, the name input 302 would identify the object and the argument input would identify the data field. In the case of a database row and column pair, the name input 302 would identify the table and the argument input 302 would identify the row and column.
The logical locking interface 301 also has a mode input 304, a lifetime input 305, a timeout input 306, and an asynchronous input 307. Each of these are described in detail immediately below.
The “mode” input 304 can specify any of the following: 1) SHARED for a read lock; 2) EXCLUSIVE for a write lock; 3) EXCLUSIVE_NON_CUMULATIVE for a write lock; 4) OPTIMISTIC for a read lock; or, 5) OPTIMISTIC_TO_EXCLUSIVE for a write lock. A description of each follows immediately below.
If a data item is experiencing a SHARED read lock by a user, other users can be given a read lock to the same data item—but—no user will be given a write lock to the data item. If a data item is experiencing an EXCLUSIVE write lock by a user other users are not given a read lock or a write lock to the data item. Cumulative means that, if a user requests an EXCLUSIVE lock for a data item that the user has already been granted an EXCLUSIVE write lock for, no “exception” will be thrown. NON CUMULATIVE means that an exception will be thrown if a user requests an EXCLUSIVE lock for a data item that the user has already received an EXCLUSIVE lock for.
An exception is a formal rejection to a lock request. Exceptions help to avoid deadlock situations. If two applications request exclusive locks for the same two data items in a different order (e.g., a first application requests item A and then item B and second application first requests item B and then item A), there might be a deadlock of these two applications. Deadlocked applications cannot proceed because, in order to proceed, they each simultaneously need access to the data that is locked by the other. In a deadlock situation, one of these applications could be stopped automatically by the application server or manually by an administrator.
To avoid such a situation, an exception is thrown if a read or write lock request cannot be granted. In response to the receiving of an exception from the logical locking interface (as a response to a read or write lock request), a user may again retry the lock request again after a short time. If the lock is still not granted, the user can retry repeatedly.
According to the OPTIMISTIC read mode, a read of the data is permitted but it is not guaranteed to be consistent with the database because other users may also be reading the same data with the intent to update (i.e., change) it. In OPTIMISTIC read locking, the first user to update the contested data “wins” because only that user is guaranteed to be consistent with the database. As such, the first “winning” user must have “propagated” the original OPTIMISTIC read into an EXCLUSIVE write. The OPTIMISTIC_TO_EXCLUSIVE mode is used for this purpose. That is, the OPTIMISTIC_TO_EXCLUSIVE mode is used when an attempt is made to update a data element that was read optimistically.
The “lifetime” input 305 specifies whether the data item is to be locked for the lifetime of a communication session; or, a transaction (local or distributed). The timeout input 306 specifies the amount of time that the logical locking interface will repeatedly try to lock a data item that, so far, has been locked by another user. Once this foreign lock is released, the lock is granted to the calling user. If the time amount given by the timeout parameter has been exceeded and the lock has not been granted to the calling user, an exception will be thrown. Therefore, a lock request call to the logical locking interface blocks the calling user until the lock is granted or the timeout time has been exceeded.
Although only locking has been discussed above, treatment as to the manner in which data items are “unlocked” can also be specified through the interface 301. According to one implementation, if the asynchronous input 307 is set to “false”, locks for a transaction or user session are released synchronously (e.g., a lock server blocks until all locks are released). By asserting the asynchronous input 307 to “true” asynchronous releases are attempted (but cannot be guaranteed).
A problem is that because the logical locking function behind the interface 301 is geared toward “something more” than traditional physical locking, detrimental effects may result if the logical locking function is used to lock an entire row of data. For example, if different users specify the row columns according to different syntaxes, the functionality behind the interface 301 might “miss” the conflict and permit overlapping requests to access the same data.